Top Machine Learning Engineer Jobs in Boston, MA

Lead the ML and AI engineering team, strategizing and implementing AI solutions for business growth, mentoring staff, and collaborating across departments.

The Machine Learning Engineer will develop and maintain scalable ML systems, collaborate across teams, and innovate solutions for real-time applications to enhance customer experiences.

Develop AI-powered solutions for personalized content and marketing. Collaborate with teams to optimize ML models and pipelines at scale, mentoring engineers and driving strategic growth initiatives.

The Machine Learning Engineer will develop and enhance search and retrieval systems, adapting search behaviors and integrating ML models for product recommendations, while managing infrastructure and data processing.

As an ML Ops Infrastructure Engineer, you will design CI/CD pipelines for ML, maintain deployment systems, and implement monitoring while collaborating with research teams to ensure model quality and performance.

The role involves building ML systems, improving models across product surfaces, and leveraging data for personalization and user engagement.

As a Machine Learning Engineer, you'll create and optimize production-ready ML solutions, manage the ML lifecycle, and conduct experiments.

As a Machine Learning Engineer, you will own the full lifecycle of ML from model development to production deployment, collaborating with teams to drive ML processes.

Design and deliver machine learning models and cloud-based systems for frontline worker devices, including model training, optimization, and deployment in cloud environments.

As a Machine Learning Engineer - Edge, you will develop and optimize AI/ML models for resource-constrained devices, collaborate with hardware engineers, and ensure model efficiency and reliability.

The Senior AI/ML Engineer at Cooley will design, build, and maintain enterprise-scale AI/ML solutions across cloud platforms, optimize performance, and collaborate on AI implementations.

The Senior Databricks AI/ML Engineer will design and deploy AI/ML solutions in the insurance sector, focusing on Databricks architecture, data pipelines, and MLOps workflows, while collaborating with various teams to operationalize models and optimize processes.

Develop and maintain scalable AI/ML architectures, collaborate on integrating solutions into products, and ensure compliance with industry standards.

As a Machine Learning Engineer, you will fine-tune transformer models, deploy machine learning solutions, and work with cross-functional teams on innovative projects.

The Senior Data Engineer will develop and deploy machine learning models, build end-to-end ML pipelines, optimize performance, and collaborate across teams to enhance AI capabilities at ClickUp.

As a Staff Machine Learning Engineer - AI Tech Lead, you will lead the design of AI systems for security operations, focusing on scalable architectures, AI safety, and mentoring. Responsibilities include overseeing technical evaluations, production workflows, LLM fine-tuning, and collaboration with teams to enhance AI capabilities.

Lead and drive strategy for generative AI projects, develop cutting-edge models, engineer data pipelines, and collaborate across teams to implement AI solutions.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

The Senior Machine Learning Engineer will design and implement ML systems, oversee data pipelines and model management, and guide technical strategy while collaborating across teams to deliver production-ready models.

As a Principal Machine Learning Engineer, you will develop distributed inference infrastructure, integrate with vLLM, and optimize inference workloads, mentoring fellow engineers along the way.

The role involves building, deploying, and maintaining ML infrastructure, optimizing systems, and ensuring production reliability while collaborating with data scientists and product teams.

Develop and optimize medical large language models, collaborate with interdisciplinary teams, and maintain state-of-the-art machine learning techniques to enhance medical education and clinical decision support.

The Machine Learning Engineer will develop and deploy computer vision models, manage ML data infrastructure, and integrate systems for autonomous aerial platforms.

As a Senior Machine Learning Engineer, you'll design and develop workflows utilizing vision-language models, manage data pipelines, and collaborate with multiple teams to enhance model accuracy and efficiency.

The Principal Data Scientist will develop algorithms using extensive datasets to improve vehicle and driver safety, mentor junior data scientists, and communicate complex concepts to stakeholders.